Journal
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
Volume 49, Issue 5, Pages 1296-1302Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jpba.2009.03.006
Keywords
Ziziphus jujuba; HPLC-DAD; Triterpenoid acid; HCA; PCA
Categories
Funding
- National Natural Science Foundation of China [30672678]
- Jiangsu College and University
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A simple and sensitive HPLC-DAD method has been developed for the first time to simultaneously determine 10 triterpenoid acids (ceanothic acid, alphitolic acid, zizyberanal acid, zizyberanalic acid, epiceanothic acid, ceanothenic acid, betulinic acid, oleanolic acid, ursonic acid and zizyberenalic acid) in the dried fruit of Ziziphus jujuba (called Dazao) which has been widely used as one of the traditional Chinese medicines (TCMs). This HPLC assay was performed on a reversed-phase C-18 column (250 mm x 4.6 mm, 5 mu m) with the column temperature at 35 degrees C. The mobile phase was composed of A (acetonitrile) and B (0.05% aqueous phosphoric acid, v/v). The flow rate was 1.0 ml/min and the detection wave length was set at 205 nm for reference compounds 1-9 and 238 nm for reference compound 10. All calibration curves showed good linear regression (r(2) > 0.9999) within the test range. The established method showed good precision and accuracy with overall intra-day and inter-day variations of 0.43-1.72% and 0.53-2.45%, respectively, and overall recoveries of 94.98-104.09% for the 10 compounds analyzed. The validated method was successfully applied for the simultaneous determination of the 10 triterpenoid acids in 42 batches of Dazao which contained 36 cultivars from 22 cultivation regions, and were investigated and authenticated as Z. jujuba. Hierarchical clustering analysis (HCA) and principal components analysis (PCA) were performed to differentiate and classify the samples based on the contents of the 10 triterpenoid acids. The presented HPLC-DAD method conjugated with chemometrics approach was demonstrated to be very helpful in using Dazao resources, and was possibly useful in chemotaxonomic characterization. (C) 2009 Elsevier B.V. All rights reserved.
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